Mass spectrometry

As for many model organisms, the amount of Listeria omics data produced has recently increased exponentially. There are now >80 published complete Listeria genomes, around 350 different transcriptomic data sets, and 25 proteomic data sets available. The analysis of these data sets through a systems biology approach and the generation of tools for biologists to browse these various data are a challenge for bioinformaticians. We have developed a web-based platform, named Listeriomics, that integrates different tools for omics data analyses, i.e., (i) an interactive genome viewer to display gene expression arrays, tiling arrays, and sequencing data sets along with proteomics and genomics data sets; (ii) an expression and protein atlas that connects every gene, small RNA, antisense RNA, or protein with the most relevant omics data; (iii) a specific tool for exploring protein conservation through the Listeria phylogenomic tree; and (iv) a coexpression network tool for the discovery of potential new regulations. Our platform integrates all the complete Listeria species genomes, transcriptomes, and proteomes published to date. This website allows navigation among all these data sets with enriched metadata in a user-friendly format and can be used as a central database for systems biology analysis.

xiNET is a visualization tool for exploring cross-linking/mass spectrometry results. The interactive maps of the cross-link network that it generates are a type of node-link diagram. In these maps xiNET displays: (1) residue resolution positional information including linkage sites and linked peptides; (2) all types of cross-linking reaction product; (3) ambiguous results; and, (4) additional sequence information such as domains. xiNET runs in a browser and exports vector graphics which can be edited in common drawing packages to create publication quality figures.

This is a novel system that enables interactive comparative visualization and analysis of metabolomics data obtained by two-dimensional gas chromatography-mass spectrometry (GCxGC-MS). This system allows the user to produce, and interactively explore, visualizations of multiple GCxGC-MS data sets, thereby allowing a user to discover differences and features in real time. This system provides statistical support in the form of mean and standard deviation calculations to aid users in identifying meaningful differences between sample groups. We combine these with multiform, linked visualizations in order to provide researchers with a powerful new tool for GCxGC-MS exploration and bio-marker discovery.

mzRepeat is a visualization system for analysing molecules with repeating structures and described visualization example of lipids obtained from MALDI-MS. This developed system can be applied to mass spectra obtained from other mass spectromy methods that have ions repeating in equal intervals, for example, in microorganism classification, synthesis polymer analysis and quality control.